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Bruce S Weir

Publications and source records attributed to Bruce S Weir.

11 recordsLinked to original sources
PubMed2024

Detecting inbreeding depression in structured populations.

Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the best method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. We simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structures (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients ([Formula: see text]) to quantify the strength of inbreeding depression: allele-sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model (LMM) including a genetic relatedness matrix (GRM) as random effect to account for the nonindependence of observations. We find LMMs give better results in scenarios with population or family structure. Within the LMM, we compare three different GRMs and show that in homogeneous populations, there is little difference among the different [Formula: see text] and GRM for inbreeding depression quantification. However, as soon as a strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if i) the phenotypes are regressed on [Formula: see text] based on a weighted version of the correlation of uniting gametes, giving more weight to common alleles and ii) with the GRM obtained from an allele-sharing relatedness estimator.

Humans↗
PubMed2006

Three major haplotypes of the beta2 adrenergic receptor define psychological profile, blood pressure, and the risk for development of a common musculoskeletal pain disorder.

Adrenergic receptor beta(2) (ADRB2) is a primary target for epinephrine. It plays a critical role in mediating physiological and psychological responses to environmental stressors. Thus, functional genetic variants of ADRB2 will be associated with a complex array of psychological and physiological phenotypes. These genetic variants should also interact with environmental factors such as physical or emotional stress to produce a phenotype vulnerable to pathological states. In this study, we determined whether common genetic variants of ADRB2 contribute to the development of a common chronic pain condition that is associated with increased levels of psychological distress and low blood pressure, factors which are strongly influenced by the adrenergic system. We genotyped 202 female subjects and examined the relationships between three major ADRB2 haplotypes and psychological factors, resting blood pressure, and the risk of developing a chronic musculoskeletal pain condition-Temporomandibular Joint Disorder (TMD). We propose that the first haplotype codes for lower levels of ADRB2 expression, the second haplotype codes for higher ADRB2 expression, and the third haplotype codes for higher receptor expression and rapid agonist-induced internalization. Individuals who carried one haplotype coding for high and one coding for low ADRB2 expression displayed the highest positive psychological traits, had higher levels of resting arterial pressure, and were about 10 times less likely to develop TMD. Thus, our data suggest that either positive or negative imbalances in ADRB2 function increase the vulnerability to chronic pain conditions such as TMD through different etiological pathways that imply the need for tailored treatment options.

Adolescent↗
PubMed2006

Evaluation of DNA pooling for the estimation of microsatellite allele frequencies: a case study using striped bass (Morone saxatilis).

Using striped bass (Morone saxatilis) and six multiplexed microsatellite markers, we evaluated procedures for estimating allele frequencies by pooling DNA from multiple individuals, a method suggested as cost-effective relative to individual genotyping. Using moment-based estimators, we estimated allele frequencies in experimental DNA pools and found that the three primary laboratory steps, DNA quantitation and pooling, PCR amplification, and electrophoresis, accounted for 23, 48, and 29%, respectively, of the technical variance of estimates in pools containing DNA from 2-24 individuals. Exact allele-frequency estimates could be made for pools of sizes 2-8, depending on the locus, by using an integer-valued estimator. Larger pools of size 12 and 24 tended to yield biased estimates; however, replicates of these estimates detected allele frequency differences among pools with different allelic compositions. We also derive an unbiased estimator of Hardy-Weinberg disequilibrium coefficients that uses multiple DNA pools and analyze the cost-efficiency of DNA pooling. DNA pooling yields the most potential cost savings when a large number of loci are employed using a large number of individuals, a situation becoming increasingly common as microsatellite loci are developed in increasing numbers of taxa.

Alleles↗
PubMed2006

Genetic relatedness analysis: modern data and new challenges.

Individuals who belong to the same family or the same population are related because of their shared ancestry. Population and quantitative genetics theory is built with parameters that describe relatedness, and the estimation of these parameters from genetic markers enables progress in fields as disparate as plant breeding, human disease gene mapping and forensic science. The large number of multiallelic microsatellite loci and biallelic SNPs that are now available have markedly increased the precision with which relationships can be estimated, although they have also revealed unexpected levels of genomic heterogeneity of relationship measures.

Animals↗
PubMed2005

It was one of my brothers.

When DNA evidence is used to implicate a suspect, it may be of interest to know whether it is likely that the suspect's near relatives also share the suspect's DNA profile. In this study we discuss methods for evaluating the probability that at least one of a set of the suspect's full or half-siblings shares the suspect's DNA profile. We present three such methods: exact calculation, estimation via Monte Carlo simulations, and estimation by means of sandwiching the probability between an upper and a lower bound. We show that, under many circumstances, this upper bound itself provides an extremely quick and accurate estimate of the probability that at least one of the relatives matches the suspect's profile.

DNA Fingerprinting↗
PubMed2005

Measures of human population structure show heterogeneity among genomic regions.

Estimates of genetic population structure (F(ST)) were constructed from all autosomes in two large SNP data sets. The Perlegen data set contains genotypes on approximately 1 million SNPs segregating in all three samples of Americans of African, Asian, and European descent; and the Phase I HapMap data set contains genotypes on approximately 0.6 million SNPs segregating in all four samples from specific Caucasian, Chinese, Japanese, and Yoruba populations. Substantial heterogeneity of F(ST) values was found between segments within chromosomes, although there was similarity between the two data sets. There was also substantial heterogeneity among population-specific F(ST) values, with the relative sizes of these values often changing along each chromosome. Population-structure estimates are often used as indicators of natural selection, but the analyses presented here show that individual-marker estimates are too variable to be useful. There is inherent variation in these statistics because of variation in genealogy even among neutral loci, and values at pairs of loci are correlated to an extent that reflects the linkage disequilibrium between them. Furthermore, it may be that the best indications of selection will come from population-specific F(ST) values rather than the usually reported population-average values.

Chromosomes, Human↗
PubMed2004

Effect of two- and three-locus linkage disequilibrium on the power to detect marker/phenotype associations.

There has been much recent interest in describing the patterns of linkage disequilibrium (LD) along a chromosome. Most empirical studies that have examined this issue have concentrated on LD between collections of pairs of markers and have not considered the joint effect of a group of markers beyond these pairwise connections. Here, we examine many different patterns of LD defined by both pairwise and joint multilocus LD terms. The LD patterns we considered were chosen in part by examining those seen in real data. We examine how changes in these patterns affect the power to detect association when performing single-marker and haplotype-based case-control tests, including a novel haplotype test based on contrasting LD between affected and unaffected individuals. Through our studies we find that differences in power between single-marker tests and haplotype-based tests in general do not appear to be large. Where moderate to high levels of multilocus LD exist, haplotype tests tend to be more powerful. Single-marker tests tend to prevail when pairwise LD is high. For moderate pairwise values and weak multilocus LD, either testing strategy may come out ahead, although it is also quite likely that neither has much power.

Case-Control Studies↗
PubMed2004

Matching and partially-matching DNA profiles.

The DNA profiles of two individuals can have 0, 1, or 2 pairs of alleles that are the same at each locus. These events may be called mismatches, partial matches or matches, respectively, and they have probabilities that depend on the population proportions of alleles as well as the population structure parameter theta. The observed and expected numbers of pairs of individuals with various numbers of matching or partially matching loci in FBI and Australian databases are found to be in good agreement provided theta is set equal to some small value greater than zero. The likelihood ratios for two individuals having a specified degree of relationship versus being unrelated also depend on the numbers of matching and partially matching loci, but even unrelated pairs of individuals can have likelihood ratios that support hypotheses of relatedness. Matching probabilities allow predictions to be made for the sizes of databases that are expected to contain a pair of individuals with high numbers of matching loci. It is very likely that two individuals with at least 9 matching loci among the 13 CODIS loci have already been typed.

DNA Fingerprinting↗
PubMed2002

Bioinformatics and approaches to identifying polygenic susceptibility traits.

The role of genetic factors in periodontal disease is now well recognized, although details for the genetic mechanisms of the disease and implications for therapy can be as obscure as they are for other human traits. This paper addresses the role that the analysis of genome-wide data might play in helping to understand the molecular determinants of periodontal risk. Very few human diseases are not polygenic, in that an individual's susceptibility depends on his or her constitution at many genetic loci, each of which may have a small effect. Not only do these loci interact, but also their actions and interactions depend on nongenetic factors. Much of the statistical machinery to handle this complexity was developed in the plant and animal breeding context, where crosses between inbred lines selected for trait differences could be conducted. Human polygenic studies began with studies on large pedigrees, but have expanded to include case-control analyses of random samples of individuals who differ in disease status, and studies of marker transmissions within nuclear families. In the area of characterizing the genetic architecture of complex traits, the relatively new field of bioinformatics is distinguished from the more mature fields of statistical genetics or genetic epidemiology by its focus on genome-wide data. The very dense sets of genetic markers now available, particularly those at single nucleotide positions (SNPs), have meant that it is possible to seek linkages or associations between chromosomal position and disease from the whole genome in a single study. Apart from the obvious problems of scale, there are real issues involved with multiple testing and recognizing interactions. Current thinking tends to focus on relatively conserved "haplotype blocks" instead of single genetic markers, although there is no consensus on the utility of this emphasis.

Dental Informatics↗